Flare phenomenon is known in digital photography, particularly occurring in the instances of bright sources of light such as the sun, positioned just outside the image frame. In single lens reflex (SLR) cameras, this often manifests as a polygonal bright region in addition to bright streaks emanating from the source of the light. In other types of cameras, the result is primarily bright streaks. For example, in camera-equipped smart phones such as Apple® iPhone® 5, some versions of iPhone® 4S, and some Android™ phones, flare artifacts take on a purple hue or purple distortion.
Purple streaks often result when a strong light source, such as the sun, is just outside of the camera's field of view. When a camera substantially faces the strong light source (at an angle) and captures an image, unwanted light from the light source enters the camera's lens and is reflected multiple times between the surfaces of the one or more lens elements of the lens, which distort the color of the light reflected thereon. The unwanted, multiple-reflected light is then captured by the image sensor behind the lens, and appears on the captured image as purple streaks.
Methods and tools for correcting purple distortion are also known. For example, Adobe® Photoshop® allows users to reduce the saturation value of a portion of an image having purple fringe to reduce purple distortion. However, while purple artifacts are reduced, nearby pixels originally unaffected by purple distortion are also modified with reduced saturation. Many professional skills are applied and developed in the attempt to correct artifacts while avoiding reducing the saturation value of pixels unaffected by purple distortion.
U.S. Pat. No. 7,577,292, entitled “Automatic Removal of Purple Fringing from Images,” to Kang, and assigned to Microsoft Corporation, discloses an automatic purple fringing removal system and method for automatically eliminating purple-fringed regions from high-resolution images. The automatic purple fringing removal system and method automatically detect a purple-fringed region in an image and then automatically correct the region. Automatic detection is achieved by finding near-saturated regions and candidate regions, and then defining a purple-fringed region as a candidate region adjacent a near-saturated region. Automatic correction of a purple-fringed region is performed by replacing color pixels in the region with at least some fully monochrome pixels using a feathering process, a monochrome averaging process, or by setting each of the red and blue intensity values by the summation of a down-scaled value of the original intensity value and a down-scaled value of the green intensity value. In short, a region is modified, including pixels not subject to the purple fringe.
An academic paper entitled “Automatic Detection and Correction of Purple Fringing Using the Gradient Information and Desaturation,” by Baek-Kyu Kim, et al., published in 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, Aug. 25-29, 2008, discloses a method to automatically detect and correct purple fringing that is one of the color artifacts due to characteristics of charge coupled device sensors in a digital camera. The disclosed method consists of two steps. The first step detects purple fringed regions that satisfy specific properties, namely hue characteristics around highlight regions with large gradient magnitudes. In the second step, color correction of the purple fringed regions is made by desaturating the pixels in the detected regions. The disclosed method can be used as a post-processing step in a digital camera.
Although the above mentioned methods can correct purple distortion to some extent, disadvantages still exist. For example, some methods require careful manual manipulation of images based on professional knowledge of photography, which applies a huge burden to users and may not be suitable for most. Some other methods exploit complex algorithms and require a computational capacity that may not be applicable to many computing systems such as smart phones and point-and-shoot digital cameras.
Therefore, there still exists a need for a system and method for easily and efficiently correcting purple distortion in digital images.